Interest Rate Sensitivity of Spanish Industries: A Quantile Regression Approach

Abstract

This paper examines the degree of interest rate exposure of Spanish industries for the period 1993–2012 using the quantile regression methodology. The empirical results show that the Spanish stock market exhibits a significant level of interest rate sensitivity, although there are notable differences across industries and over time. In addition, the impact of changes in interest rates on industry equity returns tends to be more pronounced in extreme market conditions, i.e. during crises or bubbles in stock markets, than in normal periods. This finding may be related to herding behavior of stock investors during periods of market stress.

Impact of changes in the level, slope and curvature of interest rates on U.S. sector returns: an asymmetric nonlinear cointegration approach

“…Therefore, for robustness, this study splits up the whole sample into two different sub-periods: pre subprime crisis sub-period (January 1990-December 2007 and subprime crisis sub-period (January 2008-April 2013). The division into these two consecutive sub-periods is determined by the subprime financial crisis unleashed by the fall of Lehman Brothers in September 2008 (Ferrando et al, 2017). Moreover, this division has been corroborated by the Chow breakpoint test in a N.A.R.D.L.…”

“…Finally, the interest rate is a very relevant explanatory factor, since its choice conditions the analysis (Jareño, 2006). Therefore, it has been decided to use the U.S. 10-year Treasury Bond as explanatory variable, since it has been used as a representative variable of the nominal interest rates of the North American market (Ferrando, Ferrer, & Jareño, 2017;Gonz alez, Jareño, & Skinner, 2016;Sevillano & Jareño, 2018, among others). This 10-year nominal interest rate is used in most of the investigations when incorporating future expectations, so that the price of the securities is affected.…”

Interest and Inflation Risk: Investor Behavior

“…Thus, the study of two relevant sources of risk such as interest and inflation rate movements is very interesting for deepening on the analysis of investor behavior as well as for portfolio managers. Furthermore, the recent financial crisis confirms that investor behavior changes over time (Ferrando et al, 2015 ), so this analysis is really challenging to achieve a better understanding of investor behavior. Moreover, according to Blackburn et al ( 2014 ), investor behavior may depend on different factors that affect the investment or trading decision.…”

“…The literature examines the sensitivity of stock returns to unexpected changes in nominal interest rates finding a negative and significant relationship between stock returns and unanticipated changes in nominal interest rates. See O'Neal ( 1998 ), Fraser et al ( 2002 ), Hevert et al ( 1998a , b ), Tessaromatis ( 2003 ), Jareño ( 2006 , 2008 ), Ferrer et al ( 2010 ), Korkeamäki ( 2011 ), Ferrando et al ( 2015 ), and Campos et al ( 2016 ) as examples. Some have examined these relations for the overall stock market (Elyasiani and Mansur, 1998 ; Oertmann et al, 2000 ; Shamsuddin, 2014 ) while others have mainly studied these relations for financial companies (Flannery and James, 1984 ; Fraser et al, 2002 ; Staikouras, 2003 , 2006 ; Au Yong and Faff, 2008 ; Drehmann et al, 2010 ; Ballester et al, 2011 ; Memmel, 2011 ; Bessler and Kurmann, 2012 ; Abdymomunov and Gerlach, 2014 ) or for Utilities (Sweeney and Warga, 1986 ).…”

Loom of Symmetric Pass-Through

“…Assefa et al (2017) state that the effect of interest rate changes on stock price returns is higher for developing countries than for developed countries by the panel generalized method of moments method (GMM). Ferrando et al (2017) use the quantile regression method for Spain and find a negative effect of 10-year government bond yields on stock price returns and make sectoral comparisons. Jain et al (2011) detect the negative effect of the policy rate on stock returns for Australia using the exponential generalized conditional heteroscedasticity (EGARCH) model.…”